講座內容：Challenges on Edge computing and Federated learning（邊緣計算和聯邦學習的挑戰）
講座人🦃：Hamido Fujita 教授
講座時間：11月9日 13:00-14:00
騰訊會議🏊🏼♂️：787919474
Abstract：
Edge calculation is the calculation generated near the equipment end. The definition concept of free software and open source project community licensed with Apache license: edge computing is to provide cloud services and it environment services for application developers and service providers at the edge of the network; the goal is to provide computing, storage and network bandwidth near data input or users. Edge computing needs to meet the challenges of computing resource load distribution, security, interoperability and edge operation management services. Federated learning is essentially a distributed machine learning technology. Its goal is to realize joint modeling and improve the effect of AI model on the basis of ensuring data privacy, security and legal compliance. The problems and challenges of Federated learning are: the challenges of migrating existing models, including the challenges brought by data heterogeneity and model aggregation; The challenges of distributed system setup, including cost problem, optimal resource allocation problem and multi-node communication problem; Security and privacy issues.
Short Bio：
Dr. Hamido Fujita is professor at Iwate Prefectural University (IPU), Japan, as a director of Intelligent Software Systems. He is the Editor-in-Chief of Knowledge-Based Systems, Elsevier of impact factor (3.325) for 2015. He is vice president of International Society of Applied Intelligence, and also associate Editor-in-chief of Applied Intelligence Journal (Springer). He has given many keynotes in many prestigious international conferences on intelligent system and subjective intelligence. He headed a number of projects including Intelligent HCI, a project related to Mental Cloning as an intelligent user interface between human user and computers and SCOPE project on Virtual Doctor Systems for medical applications.
